Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Development of adverse outcome pathways relevant for the identification of substances having endocrine disruption properties Uterine adenocarcinoma as adverse outcome.

Development of adverse outcome pathways (AOPs) for uterine adenocarcinoma can provide a practical tool to implement the EFSA-ECHA Guidance (2018) for the identification of endocrine disruptors in the context of Regulations (EU) No 528/2012 and (EC) No 1107/2009. AOPs can give indications about the strength of the relationship between an adverse outcome (intended as a human health outcome) and chemicals (pesticides but not only) affecting the pathways. In this scientific opinion, the PPR Panel explored the development of AOPs for uterine adenocarcinoma. An evidence-based approach methodology was applied, and literature reviews were produced using a structured framework assuring transparency, objectivity, and comprehensiveness. Several AOPs were developed; these converged to a common critical node, that is increased estradiol availability in the uterus followed by estrogen receptor activation in the endometrium; therefore, a putative AOP network was considered. An uncertainty analysis and a probabilistic quantification of the weight of evidence have been carried out via expert knowledge elicitation for each set of MIEs/KEs/KERs included in individual AOPs. The collected data on the AOP network were evaluated qualitatively, whereas a quantitative uncertainty analysis for weight of the AOP network certainty has not been performed. Recommendations are provided, including exploring further the uncertainties identified in the AOPs and putative AOP network; further methodological developments for quantifying the certainty of the KERs and of the overall AOPs and AOP network; and investigating of NAMs applications in the context of some of the MIEs/KEs currently part of the putative AOP network developed.

Is the effectiveness of policy-driven mitigation measures on carabid populations driven by landscape and farmland heterogeneity? Applying a modelling approach in the Dutch agroecosystems.

The growing challenges of protecting biodiversity in agro-ecosystems and maintaining high agricultural productivity has become an important issue within the European Union, shaping both European and national agro-policies. The presented study is part of a broader evaluation of the interim targets of the 2013 Dutch policy plan on sustainable use of pesticides, carried out in 2019 by the PBL (Planbureau voor de Leefomgeving) Netherlands Environmental Assessment Agency. We aimed to assess the effectiveness of selected mitigation measures suggested in the policy plan on non-target terrestrial arthropods using a common carabid beetle Bembidion lampros as a model species. We combined dynamic landscape models with detailed agent-based population modelling to simulate impacts of reduction of toxicity of insecticides, reduction of spray drift to the off-crop area, and increase in area of field margins on the beetle population dynamics in ten agricultural landscapes representing different farming systems. Our simulations showed that a shift towards low-risk products should be the priority if the goal is to increase beetle range. To promote local beetle abundance this needs be coupled with increasing amount of field margins in a landscape. Overall, the observed treatment and landscape effects were highly context-specific and therefore we suggest that care is used when defining and interpretting metrics based on population effects of policy measures. This caveat notwithstanding, the use of simulation to assess complex interactions between landscape, ecology and behaviour of species, and policy measures can be a powerful tool supporting innovative policy management. This should include the development of landscape-context specific targets and/or mitigation measures.

A deeper understanding of system interactions can explain contradictory field results on pesticide impact on honey bees.

While there is widespread concern regarding the impact of pesticides on honey bees, well-replicated field experiments, to date, have failed to provide clear insights on pesticide effects. Here, we adopt a systems biology approach to gain insights into the web of interactions amongst the factors influencing honey bee health. We put the focus on the properties of the system that depend upon its architecture and not on the strength, often unknown, of each single interaction. Then we test in vivo, on caged honey bees, the predictions derived from this modelling analysis. We show that the impact of toxic compounds on honey bee health can be shaped by the concurrent stressors affecting bees. We demonstrate that the immune-suppressive capacity of the widespread pathogen of bees, deformed wing virus, can introduce a critical positive feed-back loop in the system causing bistability, i.e., two stable equilibria. Therefore, honey bees under similar initial conditions can experience different consequences when exposed to the same stressor, including prolonged survival or premature death. The latter can generate an increased vulnerability of the hive to dwindling and collapse. Our conclusions reconcile contrasting field-testing outcomes and have important implications for the application of field studies to complex systems.

Supporting non-target arthropods in agroecosystems: Modelling effects of insecticides and landscape structure on carabids in agricultural landscapes.

Intensification of agricultural practices is one of the most important drivers of the dramatic decline of arthropod species. We do not know, however, the relative contribution to decline of different anthropogenic stressors that are part of this process. We used high-resolution dynamic landscape models and advanced spatially-explicit population modelling to estimate the relative importance of insecticide use and landscape structure for population dynamics of a widespread carabid beetle Bembidion lampros. The effects of in-crop mitigation measures through the application of insecticides with reduced lethality, and off-crop mitigation measures by increasing abundance of grassy field margins, were evaluated for the beetle along the gradient of landscape heterogeneity. Reducing the insecticide-driven lethality (from 90 to 10%) had larger positive impacts on beetle density and occupancy than increasing the abundance of field margins in a landscape. The effects of increasing field margins depended on their width and overall abundance in the landscape, but only field margins 4 m wide, applied to at least 40% of fields, resulted in an increase in beetle population density comparable to the scenario with the smallest reduction of insecticide-driven lethality we considered. Our findings suggest the importance of field margins rather as a supporting not stand-alone mitigation measure, as they generally improved effects of reduction of insecticide-driven lethality. Therefore, adding sufficiently broad off-field habitats should help to maintain viable beetle populations in agricultural landscapes even with moderate use of insecticides. In general, the less persistent the insecticides are in the environment, the larger positive impacts of applied mitigation measures on beetle populations were found. We also showed that the effectiveness of applied mitigation measures strongly depends on landscape and farmland heterogeneity. Thus, to achieve the same management or mitigation target in different landscapes might require different strategies.

Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on testing and interpretation of comparative in vitro metabolism studies.

EFSA asked the Panel on Plant Protection Products and their residues to deliver a Scientific Opinion on testing and interpretation of comparative in vitro metabolism studies for both new active substances and existing ones. The main aim of comparative in vitro metabolism studies of pesticide active substances is to evaluate whether all significant metabolites formed in the human in vitro test system, as a surrogate of the in vivo situation, are also present at comparable level in animal species tested in toxicological studies and, therefore, if their potential toxicity has been appropriately covered by animal studies. The studies may also help to decide which animal model, with regard to a particular compound, is the most relevant for humans. In the experimental strategy, primary hepatocytes in suspension or culture are recommended since hepatocytes are considered the most representative in vitro system for prediction of in vivo metabolites. The experimental design of 3 × 3 × 3 (concentrations, time points, technical replicates, on pooled hepatocytes) will maximise the chance to identify unique (UHM) and disproportionate (DHM) human metabolites. When DHM and UHM are being assessed, test item-related radioactivity recovery and metabolite profile are the most important parameters. Subsequently, structural characterisation of the assigned metabolites is performed with appropriate analytical techniques. In toxicological assessment of metabolites, the uncertainty factor approach is the first alternative to testing option, followed by new approach methodologies (QSAR, read-across, in vitro methods), and only if these fail, in vivo animal toxicity studies may be performed. Knowledge of in vitro metabolites in human and animal hepatocytes would enable toxicological evaluation of all metabolites of concern, and, furthermore, add useful pieces of information for detection and evaluation of metabolites in different matrices (crops, livestock, environment), improve biomonitoring efforts via better toxicokinetic understanding, and ultimately, develop regulatory schemes employing physiologically based or physiology-mimicking in silico and/or in vitro test systems to anticipate the exposure of humans to potentially hazardous substances in plant protection products.

Statement on the translocation potential by Pseudomonas chlororaphis MA342 in plants after seed treatment of cereals and peas and assessment of the risk to humans.

The European Commission requested EFSA to provide scientific advice on the translocation potential by Pseudomonas chlororaphis MA342 in plants after seed treatment of cereals and peas and, if applicable, for a revision of the assessment of the risk to humans by its metabolite 2,3-deepoxy-2,3-didehydro-rhizoxin (DDR) and this based on the evidence available in the dossier for renewal of the approval. The information from other P. chlororaphis strains than MA342 was taken into account with care, because the studies available in the dossier did not confirm the identity of the strain MA342 as belonging to the species P. chlororaphis. It has been concluded that there is a potential for translocation of P. chlororaphis MA342 to edible plant parts following seed treatment till an estimated concentration up to about 105 cfu/g and some exposure can be assumed by consumption of fresh commodities. Also, production of the metabolite DDR in the plant cannot be excluded. Regarding levels of DDR in the raw agricultural commodities, exposure estimates based on the limit of quantification (LOQ) for DDR in cereals cannot be further refined while there is no information on the levels of DDR in peas in the dossier. As regards genotoxicity, DDR induced chromosomal damage; however, it was not possible to conclude whether it is through an aneugenic or clastogenic mechanism. Hence, it is not possible to draw a reliable conclusion that DDR is producing an aneugenic effect nor to determine a threshold dose for aneugenicity. Thus, it is not possible to revise the human risk assessment as regards exposure to DDR. The concerns identified in the EFSA conclusion of 2017 remain.

Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on the genotoxic potential of triazine amine (metabolite common to several sulfonylurea active substances).

The Panel received a mandate from the European Commission to assess the genotoxic potential of triazine amine based on available information submitted by the applicants. Available information includes experimental genotoxicity data on triazine amine, Quantitative Structure-Activity Relationship (QSAR) analysis and read across with structurally similar compounds. Based on the overall weight of evidence, the Panel, in agreement with the cross-cutting Working Group Genotoxicity, concluded that there is no concern for the potential of triazine amine to induce gene mutations and clastogenicity; however, the potential to induce aneugenicity was not adequately investigated. For a conclusion, an in vitro micronucleus assay performed with triazine amine would be needed.

European hares do not avoid newly pesticide-sprayed fields: Overspray as unnoticed pathway of pesticide exposure.

Although risk assessments for pesticides involve quantifying exposure routes for animals, little empirical evidence exists on how individuals use areas where pesticides were used. Further, the European Food Safety Authority guidelines for the risk assessment of birds and mammals currently only include direct dietary uptake from exposed plants as important pathway for pesticides, arguing that dermal exposure is generally negligible. Here, we use the European hare (Lepus europaeus) as a model of a farmland specialist to investigate if (1) hares adjust habitat use in response to pesticide spraying, using GPS data, and (2) calculate the pesticide exposure and uptake over different pathways, i.e. foraging uptake versus overspray and subsequent oral grooming, using an agent-based modelling approach. Apart from avoidance of sprayed fields on the spraying day by inactive hares, which was likely caused by the mechanical disturbance rather than the pesticide itself, we found no evidence that hares reduced the use of pesticide-sprayed fields compared to control observations where no pesticides were applied. Our simulation showed that both the proportion of exposed individuals and the pesticide uptake were related to the pathway of exposure (foraging versus overspray/oral grooming), and depended on the age class and the vegetation type. We found that pesticide uptake via overspray/oral grooming might be 7-fold higher compared to foraging and might thus be an important pathway of pesticide exposure in hares. Our findings emphasize that policy makers, specifically the European Food Safety Authority, should incorporate alternative pathways of pesticide exposure for birds and mammals, such as overspray and oral grooming, when conducting environmental risk assessments and take variation in vegetation structure and age-related animal behavior into account, because these factors might affect pesticide exposure. Interactions between pesticide application and vegetation structure may both increase or decrease exposure but can be predicted using a simulation approach.

Wing membrane and fur samples as reliable biological matrices to measure bioaccumulation of metals and metalloids in bats.

There is a growing conservation concern about the possible consequences of environmental contamination in the health of bat communities. Most studies on the effects of contaminants in bats have been focused on organic contaminants, and the consequences of bat exposure to metals and metalloids remain largely unknown. The aim of this study was to evaluate the suitability of external biological matrices (fur and wing membrane) for the assessment of exposure and bioaccumulation of metals in bats. The concentration of arsenic, cadmium, cobalt, chromium, copper, manganese, nickel, lead, selenium and zinc was measured in internal organs (liver, heart, brain), internal (bone) and external tissues (wing membrane, fur) collected from bat carcasses of four species (Hypsugo savii, Nyctalus leisleri, Pipistrellus pipistrellus, Pipistrellus pygmaeus) obtained in windfarm mortality searches. With the exception of zinc (P = 0.223), the results showed significant differences between the concentrations of metals in the analyzed tissues for all metals (P < 0.05). Significant differences were also found between organs/tissues (P < 0.001), metals (P < 0.001) and a significant interaction between organs/tissues and metals was found (P < 0.001). Despite these results, the patterns in terms of metal accumulation were similar for all samples. Depending on the metal, the organ/tissue that showed the highest concentrations varied, but fur and wing had the highest concentrations for most metals. The variability obtained in terms of metal concentrations in different tissues highlights the need to define standardized methods capable of being applied in monitoring bat populations worldwide. The results indicate that wing membrane and fur, biological matrices that may be collected from living bats, yield reliable results and may be useful for studies on bats ecotoxicology, coupled to a standardized protocol for large-scale investigation of metal accumulation.

Using problem formulation for fit-for-purpose pre-market environmental risk assessments of regulated stressors.

Pre-market/prospective environmental risk assessments (ERAs) contribute to risk analyses performed to facilitate decisions about the market introduction of regulated stressors. Robust ERAs begin with an explicit problem formulation, which involves among other steps: (1) formally devising plausible pathways to harm that describe how the deployment of a regulated stressor could be harmful; (2) formulating risk hypotheses about the likelihood and severity of such events; (3) identifying the information that will be useful to test the risk hypotheses; and (4) developing a plan to acquire new data for hypothesis testing should tests with existing information be insufficient for decision-making. Here, we apply problem formulation to the assessment of possible adverse effects of RNA interference-based insecticidal genetically modified (GM) plants, GM growth hormone coho salmon, gene drive-modified mosquitoes and classical biological weed control agents on non-target organisms in a prospective manner, and of neonicotinoid insecticides on bees in a retrospective manner. In addition, specific considerations for the problem formulation for the ERA of nanomaterials and for landscape-scale population-level ERAs are given. We argue that applying problem formulation to ERA maximises the usefulness of ERA studies for decision-making, through an iterative process, because: (1) harm is defined explicitly from the start; (2) the construction of risk hypotheses is guided by policy rather than an exhaustive attempt to address any possible differences; (3) existing information is used effectively; (4) new data are collected with a clear purpose; (5) risk is characterised against well-defined criteria of hypothesis corroboration or falsification; and (6) risk assessment conclusions can be communicated clearly. However, problem formulation is still often hindered by the absence of clear policy goals and decision-making criteria (e.g. definition of protection goals and what constitutes harm) that are needed to guide the interpretation of scientific information. We therefore advocate further dialogue between risk assessors and risk managers to clarify how ERAs can address policy goals and decision-making criteria. Ideally, this dialogue should take place for all classes of regulated stressors, as this can promote alignment and consistency on the desired level of protection and maximum tolerable impacts across regulated stressors.

Scientific opinion on pesticides in foods for infants and young children.

Following a request from the European Commission, the EFSA Panel on Plant Protection Products and their Residues (PPR Panel) prepared a scientific opinion to provide a comprehensive evaluation of pesticide residues in foods for infants and young children. In its approach to develop this scientific opinion, the EFSA PPR Panel took into account, among the others, (i) the relevant opinions of the Scientific Committee for Food setting a default maximum residue level (MRL) of 0.01 mg/kg for pesticide residues in foods for infants and young children; (ii) the recommendations provided by EFSA Scientific Committee in a guidance on risk assessment of substances present in food intended for infants below 16 weeks of age; (iii) the knowledge on organ/system development in infants and young children. For infants below 16 weeks of age, the EFSA PPR Panel concluded that pesticide residues at the default MRL of 0.01 mg/kg for food for infants and young children are not likely to result in an unacceptable exposure for active substances for which a health-based guidance value (HBGV) of 0.0026 mg/kg body weight (bw) per day or higher applies. Lower MRLs are recommended for active substances with HBGVs below this value. For infants above 16 weeks of age and young children, the established approach for setting HBGVs is considered appropriate. For infants below 16 weeks of age the approach may not be appropriate and the application of the EFSA guidance on risk assessment of substances present in food intended for infants below 16 weeks of age is recommended. The contribution of conventional food to the total exposure to pesticide residues is much higher than that from foods intended for infants and young children. Because of the increased intake of conventional food by young children, these have the highest exposure to pesticide residues, whereas infants 3-6 months of age generally have lower exposure. The impact of cumulative exposure to pesticide residues on infants and young children is not different from the general population and the EFSA cumulative risk assessment methodology is also applicable to these age groups. Residue definitions established under Regulation (EC) No 396/2005 are in general considered appropriate also for foods for infants and young children. However, based on a tier 1 analysis of the hydrolysis potential of pesticides simulating processing, the particular appropriateness of existing residue definitions for monitoring to cover processed food, both intended for infants and young children as well as conventional food, is questionable.

Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms.

Following a request from EFSA, the Panel on Plant Protection Products and their Residues (PPR) developed an opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) models and their use in prospective environmental risk assessment (ERA) for pesticides and aquatic organisms. TKTD models are species- and compound-specific and can be used to predict (sub)lethal effects of pesticides under untested (time-variable) exposure conditions. Three different types of TKTD models are described, viz., (i) the 'General Unified Threshold models of Survival' (GUTS), (ii) those based on the Dynamic Energy Budget theory (DEBtox models), and (iii) models for primary producers. All these TKTD models follow the principle that the processes influencing internal exposure of an organism, (TK), are separated from the processes that lead to damage and effects/mortality (TD). GUTS models can be used to predict survival rate under untested exposure conditions. DEBtox models explore the effects on growth and reproduction of toxicants over time, even over the entire life cycle. TKTD model for primary producers and pesticides have been developed for algae, Lemna and Myriophyllum. For all TKTD model calibration, both toxicity data on standard test species and/or additional species can be used. For validation, substance and species-specific data sets from independent refined-exposure experiments are required. Based on the current state of the art (e.g. lack of documented and evaluated examples), the DEBtox modelling approach is currently limited to research applications. However, its great potential for future use in prospective ERA for pesticides is recognised. The GUTS model and the Lemna model are considered ready to be used in risk assessment.

Exposure of stone marten (Martes foina) and polecat (Mustela putorius) to anticoagulant rodenticides: Effects of regulatory restrictions of rodenticide use.

When anticoagulant rodenticides (ARs) are used to control rodent populations there is also a widespread secondary exposure of non-target predators to ARs. To reduce secondary exposure, regulatory restrictions in AR usage were tightened in Denmark in 2011. The restrictions included the cessation of AR use for plant protection and any use away from buildings, as well as limitations in private consumers' access to ARs. To quantify and evaluate the efficiency of the regulatory measures to reduce secondary exposure, we analysed ARs in liver tissue from 40 stone martens (Martes foina) and 40 polecats (Mustela putorius) collected before and 31 stone martens and 29 polecats collected after the restrictions were imposed. No declines in the prevalence ARs were detected following the regulatory restrictions in either stone marten (Before: 98%, After: 100%) or polecat (Before: 93%, After: 97%). The total AR concentration was higher in stone martens than in polecats in both sampling periods. Between the two sampling periods, the total AR concentrations in the mustelids increased (P<0.001). The increase was significant for stone marten (Before: 419ng/g ww, After: 1116ng/g ww, P<0.001), but not for polecat (Before: 170ng/g ww, After: 339ng/g ww). Overall, the total AR concentration was positively correlated to the urban area and the area used for Christmas tree production in which ARs were regularly used before 2011. The regulatory restrictions in AR usage did not reduce exposure of non-target stone martens and polecats. The temporal and spatial patterns of AR concentrations in predators indicate that chemical rodent control in and around buildings is the dominant source for the exposure of non-target predators in intensively human-dominated landscapes in Denmark. The results suggest that non-chemical methods for rodents control at buildings are necessary to prevent widespread secondary AR exposure of predators in human modified landscapes.

Per Aspera ad Astra: Through Complex Population Modeling to Predictive Theory.

Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam's razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam's razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.

Modelling Skylarks (Alauda arvensis) to predict impacts of changes in land management and policy: development and testing of an agent-based model.

Agent-based simulation models provide a viable approach for developing applied models of species and systems for predictive management. However, there has been some reluctance to use these models for policy applications due to complexity and the need for improved testing and communication of the models. We present the development and testing of a comprehensive model for Skylark (Alauda arvensis) in Danish agricultural landscapes. The model is part of the ALMaSS system, which considers not only individual skylarks, but also the detailed dynamic environment from which they obtain the information necessary to simulate their behaviour. Population responses emerge from individuals interacting with each other and the environment. Model development and testing was carried out using pattern-oriented modelling. The testing procedure was based on the model's ability to represent detailed real world patterns of distribution and density, reproductive performance and seasonal changes in territory numbers. Data to support this was collected over a 13-year period and comprised detailed field observations of breeding birds and intensive surveys. The model was able to recreate the real world data patterns accurately; it was also able to simultaneously fit a number of other secondary system properties which were not formally a part of the testing procedure. The correspondence of model output to real world data and sensitivity analysis are presented and discussed, and the model's description is provided in ODdox format (a formal description inter-linked to the program code). Detailed and stringent tests for model performance were carried out, and standardised model description and open access to the source code were provided to open development of the skylark model to others. Over and above documenting the utility of the model, this open process is essential to engender the user trust and ensure continued development of these comprehensive systems for applied purposes.

Post-hoc pattern-oriented testing and tuning of an existing large model: lessons from the field vole.

Pattern-oriented modeling (POM) is a general strategy for modeling complex systems. In POM, multiple patterns observed at different scales and hierarchical levels are used to optimize model structure, to test and select sub-models of key processes, and for calibration. So far, POM has been used for developing new models and for models of low to moderate complexity. It remains unclear, though, whether the basic idea of POM to utilize multiple patterns, could also be used to test and possibly develop existing and established models of high complexity. Here, we use POM to test, calibrate, and further develop an existing agent-based model of the field vole (Microtus agrestis), which was developed and tested within the ALMaSS framework. This framework is complex because it includes a high-resolution representation of the landscape and its dynamics, of the individual's behavior, and of the interaction between landscape and individual behavior. Results of fitting to the range of patterns chosen were generally very good, but the procedure required to achieve this was long and complicated. To obtain good correspondence between model and the real world it was often necessary to model the real world environment closely. We therefore conclude that post-hoc POM is a useful and viable way to test a highly complex simulation model, but also warn against the dangers of over-fitting to real world patterns that lack details in their explanatory driving factors. To overcome some of these obstacles we suggest the adoption of open-science and open-source approaches to ecological simulation modeling.

The effects of landscape modifications on the long-term persistence of animal populations.

BACKGROUND: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. METHODOLOGY/PRINCIPAL FINDINGS: Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. SIGNIFICANCE: Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.

The effects of spatial and temporal heterogeneity on the population dynamics of four animal species in a Danish landscape.

BACKGROUND: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. RESULTS: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23-30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3-13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. CONCLUSION: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.